code: def ndtr(x, name="ndtr"):
      """Normal distribution function.
  
      Returns the area under the Gaussian probability density function, integrated
      from minus infinity to x:
  
      ```
                        1       / x
         ndtr(x)  = ----------  |    exp(-0.5 t**2) dt
                    sqrt(2 pi)  /-inf
  
                  = 0.5 (1 + erf(x / sqrt(2)))
                  = 0.5 erfc(x / sqrt(2))
      ```
  
      Args:
        x: `Tensor` of type `float32`, `float64`.
        name: Python string. A name for the operation (default="ndtr").
  
      Returns:
        ndtr: `Tensor` with `dtype=x.dtype`.
  
      Raises:
        TypeError: if `x` is not floating-type.
      """
  
      with tf.name_scope(name):
          x = tf.convert_to_tensor(x, name="x")
          if dtype_util.as_numpy_dtype(x.dtype) not in [
              np.float32,
              np.float64,
          ]:
              raise TypeError(
                  "x.dtype=%s is not handled, see docstring for supported types."
                  % x.dtype
              )
          return _ndtr(x)
  
file_path: probability/tensorflow_probability/python/internal/special_math.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
label_desc: Use image node_id 1 for calling a global function with example usage: ndtr(x, name) and returns: _ndtr